Documentation/4.1/Modules/BRAINSFit - Revision history

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{{documentation/{{documentation/version}}/module-header}}



{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}
{{documentation/{{documentation/version}}/module-introduction-row}}
This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on NA-MIC can be obtained from the [http://www.na-mic.org/ NA-MIC website]. 
Author: Hans Johnson, UIOWA 
Contributor1: Kent Williams, UIOWA 
Contributor2: Vincent Magnotta, UIOWA 
Contributor3: Andriy Fedorov, BWH 
Contact: Hans Johnson, <email>(hans-johnson@uiowa.edu</email> 
{{documentation/{{documentation/version}}/module-introduction-row}}
{{documentation/{{documentation/version}}/module-introduction-logo-gallery
|Image:UIOWA-logo.png|University of Iowa
|Image:Logo-splnew.jpg|Surgical Planning Laboratory
}}
{{documentation/{{documentation/version}}/module-introduction-end}}


{{documentation/{{documentation/version}}/module-section|Module Description}}
{{documentation/{{documentation/version}}/module-description}}


{{documentation/{{documentation/version}}/module-section|Use Cases}}
Most frequently used for these scenarios:

* '''''Use Case 1: Same Subject: Longitudinal'''''

For this use case we're registering a baseline T1 scan with a follow-up T1 scan on the same subject a year later. The two images are again available on [http://midas.kitware.com/item/view/483 Midas] as testT1.nii.gz and testT1Longitudinal.nii.gz

First we set the fixed and moving volumes as well as the output transform and output volume names.
<pre>
--fixedVolume testT1.nii.gz \
--movingVolume testT1Longitudinal.nii.gz \
--outputVolume testT1LongRegFixed.nii.gz \
--outputTransform longToBase.xform \
</pre>
Since these are the same subject and very little has likely changed in the last year we'll use a Rigid registration. If the registration is poor or there are reasons to expect anatomical changes then additional transforms may be needed, in which case they can be added in a comma separated list, such as "Rigid,ScaleVersor3D,ScaleSkewVersor3D,Affine,BSpline".
<pre>
--transformType Rigid \
</pre>
The scans are the same modality so we'll use --histogramMatch to match the intensity profiles as this tends to help registration. If there are lesions or tumors that vary between images this may not be a good idea, as it will make it harder to detect differences between the images.
<pre>
--histogramMatch \
</pre>
To start with the best possible initial alignment we use --initializeTransformMode. We're working with human heads so we pick useCenterOfHeadAlign, which detects the center of head even with varying amounts of neck or shoulders present.
<pre>
--initializeTransformMode useCenterOfHeadAlign \
</pre>
ROI masks normally improve registration but we haven't generated any so we turn on --maskProcessingMode ROIAUTO.
<pre>
--maskProcessingMode ROIAUTO \
</pre>
The registration generally performs better if we include some background in the mask that way the tissue boundary is very clear. The parameter that expands the mask outside the brain is ROIAutoDilateSize (under Registration Debugging Parameters if using the GUI). These values are in millimeters so a good starting value is 3.
<pre>
--ROIAutoDilateSize 3 \
</pre>
Last we set the interpolation mode to be Linear, which is a decent tradeoff between quality and speed. If the best possible interpolation is needed regardless of processing time, select WindowedSync instead of linear.
<pre>
--interpolationMode Linear
</pre>

The full command is:
<pre>
BRAINSFit --fixedVolume testT1.nii.gz \
--movingVolume testT1Longitudinal.nii.gz \
--outputVolume testT1LongRegFixed.nii.gz \
--outputTransform longToBase.xform \
--transformType Rigid \
--histogramMatch \
--initializeTransformMode useCenterOfHeadAlign \
--maskProcessingMode ROIAUTO \
--ROIAutoDilateSize 3 \
--interpolationMode Linear
</pre>

{|
| [[Image:LongitudinalCheckerboardPreReg.png|thumb|180px|Longitudinal Checkerboard Before registration]]
| [[Image:LogitudinalCheckerboardPostReg.png|thumb|180px|Longitudinal Checkerboard After registration]]
|}

* '''''Use Case 2: Same Subject: MultiModal'''''

For this use case we're registering a T1 scan with a T2 scan collected in the same session. The two images are again available on [http://midas.kitware.com/item/view/483 Midas] as testT1.nii.gz and testT2.nii.gz

First we set the fixed and moving volumes as well as the output transform and output volume names.
<pre>
--fixedVolume testT1.nii.gz \
--movingVolume testT2.nii.gz \
--outputVolume testT2RegT1.nii.gz \
--outputTransform T2ToT1.xform \
</pre>
Since these are the same subject, same session we'll use a Rigid registration.
<pre>
--transformType Rigid \
</pre>
The scans are different modalities so we absolutely DO NOT want to use --histogramMatch to match the intensity profiles as this would try to map the T2 intensities into T1 intensities, resulting in an image that was neither, and hence useless.

To start with the best possible initial alignment we use --initializeTransformMode. We're working with human heads so we pick useCenterOfHeadAlign, which detects the center of head even with varying amounts of neck or shoulders present.
<pre>
--initializeTransformMode useCenterOfHeadAlign \
</pre>
ROI masks normally improve registration but we haven't generated any so we turn on --maskProcessingMode ROIAUTO.
<pre>
--maskProcessingMode ROIAUTO \
</pre>
The registration generally performs better if we include some background in the mask that way the tissue boundary is very clear. The parameter that expands the mask outside the brain is ROIAutoDilateSize (under Registration Debugging Parameters if using the GUI). These values are in millimeters so a good starting value is 3.
<pre>
--ROIAutoDilateSize 3 \
</pre>
Last we set the interpolation mode to be Linear, which is a decent tradeoff between quality and speed. If the best possible interpolation is needed regardless of processing time, select WindowedSync instead of linear.
<pre>
--interpolationMode Linear
</pre>

The full command is:
<pre>
BRAINSFit --fixedVolume testT1.nii.gz \
--movingVolume testT2.nii.gz \
--outputVolume testT2RegT1.nii.gz \
--outputTransform T2ToT1.xform \
--transformType Rigid \
--initializeTransformMode useCenterOfHeadAlign \
--maskProcessingMode ROIAUTO \
--ROIAutoDilateSize 3 \
--interpolationMode Linear
</pre>

{|
| [[Image:T1T2PreRegCheckerboard.png|thumb|180px|Multimodal Checkerboard Before registration]]
| [[Image:T1T2RegCheckerboard.png|thumb|180px|Multimodal Checkerboard After registration]]
|}

* '''''Use Case 3: Mouse Registration'''''

Here we'll register brains from two different mice together. The fixed and moving mouse brains used in this example are available on [http://midas.kitware.com/item/view/483 Midas].

First we set the fixed and moving volumes as well as the output transform and output volume names.
<pre>
--fixedVolume mouseFixed.nii.gz \
--movingVolume mouseMoving.nii.gz \
--outputVolume movingRegFixed.nii.gz \
--outputTransform movingToFixed.xform \
</pre>
Since the subjects are different we are going to use transforms all the way through BSpline. Again, building up transforms one type at a time can't hurt and might help, so we're including all transforms from Rigid through BSpline in the transformType parameter.
<pre>
--transformType Rigid,ScaleVersor3D,ScaleSkewVersor3D,Affine,BSpline \
</pre>
The scans are the same modality so we'll use --histogramMatch.
<pre>
--histogramMatch \
</pre>
To start with the best possible initial alignment we use --initializeTransformMode but we are't working with human heads so we can't pick useCenterOfHeadAlign. Instead we pick useMomentsAlign which does a reasonable job of selecting the centers of mass.
<pre>
--initializeTransformMode useMomentsAlign \
</pre>
ROI masks normally improve registration but we haven't generated any so we turn on --maskProcessingMode ROIAUTO.
<pre>
--maskProcessingMode ROIAUTO \
</pre>
Since the mouse brains are much smaller than human brains there are a few advanced parameters we'll need to tweak, ROIAutoClosingSize and ROIAutoDilateSize (both under Registration Debugging Parameters if using the GUI). These values are in millimeters so a good starting value for mice is 0.9.
<pre>
--ROIAutoClosingSize 0.9 \
--ROIAutoDilateSize 0.9 \
</pre>
Last we set the interpolation mode to be Linear, which is a decent tradeoff between quality and speed. If the best possible interpolation is needed regardless of processing time, select WindowedSync instead of linear.
<pre>
--interpolationMode Linear
</pre>

The full command is:
<pre>
BRAINSFit --fixedVolume mouseFixed.nii.gz \
--movingVolume mouseMoving.nii.gz \
--outputVolume movingRegFixed.nii.gz \
--outputTransform movingToFixed.xform \
--transformType Rigid,ScaleVersor3D,ScaleSkewVersor3D,Affine,BSpline \
--histogramMatch \
--initializeTransformMode useMomentsAlign \
--maskProcessingMode ROIAUTO \
--ROIAutoClosingSize 0.9 \
--ROIAutoDilateSize 0.9 \
--interpolationMode Linear
</pre>

{|
| [[Image:MouseCheckerboardPreRegistration.png|thumb|180px|Mouse Checkerboard Before registration]]
| [[Image:MouseCheckerboardPostRegistration.png|thumb|180px|Mouse Checkerboard After registration]]
|}


{{documentation/{{documentation/version}}/module-section|Tutorials}}
Links to tutorials that use this module


{{documentation/{{documentation/version}}/module-section|Panels and their use}}
{{documentation/{{documentation/version}}/module-parametersdescription}}


{{documentation/{{documentation/version}}/module-section|Similar Modules}}
* Point to other modules that have similar functionality


{{documentation/{{documentation/version}}/module-section|References}}
* [http://hdl.handle.net/1926/1291 BRAINSFit: Mutual Information Registrations of Whole-Brain 3D Images, Using the Insight Toolkit], Johnson H.J., Harris G., Williams K., The Insight Journal, 2007.
* Source repository on [https://github.com/BRAINSia/BRAINSStandAlone/tree/master/BRAINSFit github]
For extensions: link to the source code repository and additional documentation


{{documentation/{{documentation/version}}/module-section|Information for Developers}}
{{documentation/{{documentation/version}}/module-developerinfo}}


{{documentation/{{documentation/version}}/module-footer}}

← Older revision		Revision as of 07:27, 14 June 2013
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	{{documentation/{{documentation/version}}/module-header}}		{{documentation/{{documentation/version}}/module-header}}

@@ Line 28: / Line 28: @@
 # '''''Same Subject: Longitudinal'''''
-For this case we're registering a baseline T1 scan with a follow-up T1 scan on the same subject a year later.  The two images are available on [http://midas.kitware.com/item/view/483 Midas] as testT1.nii.gz and testT1Longitudinal.nii.gz
+For this case we're registering a baseline T1 scan with a follow-up T1 scan on the same subject a year later.  The two images are available on the [http://midas.kitware.com/item/view/483 Midas site] as test.nii.gz and test2.nii.gz
 First, set the fixed and moving volumes:
 <pre>
---fixedVolume testT1.nii.gz \
+--fixedVolume test.nii.gz \
---movingVolume testT1Longitudinal.nii.gz \
+--movingVolume test2.nii.gz \
 </pre>
 Next, set the output transform and volume:
@@ Line 82: / Line 82: @@
 The full command is:
 <pre>
-BRAINSFit --fixedVolume testT1.nii.gz \
+BRAINSFit --fixedVolume test.nii.gz \
---movingVolume testT1Longitudinal.nii.gz \
+--movingVolume test2.nii.gz \
 --outputVolume testT1LongRegFixed.nii.gz \
 --outputTransform longToBase.xform \
@@ Line 101: / Line 101: @@
 # '''''Same Subject: MultiModal'''''
-For this use case we're registering a T1 scan with a T2 scan collected in the same session.  The two images are again available on [http://midas.kitware.com/item/view/483 Midas] as testT1.nii.gz and testT2.nii.gz
+For this use case we're registering a T1 scan with a T2 scan collected in the same session.  The two images are again available on the [http://midas.kitware.com/item/view/483 Midas site] as test.nii.gz and standard.nii.gz
 First we set the fixed and moving volumes as well as the output transform and output volume names.
 <pre>
---fixedVolume testT1.nii.gz \
+--fixedVolume test.nii.gz \
---movingVolume testT2.nii.gz \
+--movingVolume standard.nii.gz \
 --outputVolume testT2RegT1.nii.gz \
 --outputTransform T2ToT1.xform \
@@ Line 135: / Line 135: @@
 The full command is:
 <pre>
-BRAINSFit --fixedVolume testT1.nii.gz \
+BRAINSFit --fixedVolume test.nii.gz \
---movingVolume testT2.nii.gz \
+--movingVolume standard.nii.gz \
 --outputVolume testT2RegT1.nii.gz \
 --outputTransform T2ToT1.xform \
@@ Line 153: / Line 153: @@
 * '''''Mouse Registration'''''
-Here we'll register brains from two different mice together.  The fixed and moving mouse brains used in this example are available on [http://midas.kitware.com/item/view/483 Midas].
+Here we'll register brains from two different mice together.  The fixed and moving mouse brains used in this example are available on the [http://midas.kitware.com/item/view/483 Midas site] as mouseFixed.nii.gz and mouseMoving.nii.gz.
 First we set the fixed and moving volumes as well as the output transform and output volume names.

@@ Line 214: / Line 214: @@
 <!-- ---------------------------- -->
 {{documentation/{{documentation/version}}/module-section|Information for Developers}}
-{{documentation/{{documentation/version}}/module-developerinfo | BRAINSFit | amboxType = notice | image = [[Image:UIOWA-logo.png|40px|Iowa logo]] | category = Registration | text = See details above.}}
+{{documentation/{{documentation/version}}/module-developerinfo-UIowa | BRAINSFit | Registration | See details above.}}

@@ Line 231: / Line 231: @@
 * [http://hdl.handle.net/1926/1291 BRAINSFit: Mutual Information Registrations of Whole-Brain 3D Images, Using the Insight Toolkit], Johnson H.J., Harris G., Williams K., The Insight Journal, 2007.
 * Source repository on [https://github.com/BRAINSia/BRAINSStandAlone/tree/master/BRAINSFit github]
 <!-- ---------------------------- -->